RTU Zinātniskās darbības rezultāti un resursi: Personāls

Publikācijas

Atrasti 4 rezultāti tiek attēloti no 1 līdz 4.

A Review for Pre-Trained Transformer-Based Time Series Forecasting Models
(2023)

Yunus Emre Midilli, Sergejs Paršutins
Publikācijas konferenču materiālos, kas ir indeksēti Web of Science un/vai SCOPUS

Design of Experiments vs. TOPSIS to Select Hyperparameters of Neural Attention Models in Time Series Prediction
(2020)

Yunus Emre Midilli, Sergejs Paršutins
Anonīmi recenzēts zinātniskais raksts, kas publicēts izdevumā ar starptautisku redkolēģiju un pieejams citā indeksētā datu bāzē

Review for Optimisation of Neural Networks with Genetic Algorithms and Design of Experiments in Stock Market Prediction
(2019)

Sergejs Paršutins, Yunus Emre Midilli
Anonīmi recenzēts zinātniskais raksts, kas publicēts izdevumā ar starptautisku redkolēģiju un pieejams citā indeksētā datu bāzē

Optimization of Neural Networks with Response Surface Methodology: Prediction of Cigarette Pressure Drop
(2019)

Yunus Emre Midilli, Sermin Elevli
Publikācijas konferenču materiālos, kas ir indeksēti Web of Science un/vai SCOPUS

Informācija par autoru

Publikācijas

A Review for Pre-Trained Transformer-Based Time Series Forecasting Models (2023)

Design of Experiments vs. TOPSIS to Select Hyperparameters of Neural Attention Models in Time Series Prediction (2020)

Review for Optimisation of Neural Networks with Genetic Algorithms and Design of Experiments in Stock Market Prediction (2019)

Optimization of Neural Networks with Response Surface Methodology: Prediction of Cigarette Pressure Drop (2019)

A Review for Pre-Trained Transformer-Based Time Series Forecasting Models
(2023)

Design of Experiments vs. TOPSIS to Select Hyperparameters of Neural Attention Models in Time Series Prediction
(2020)

Review for Optimisation of Neural Networks with Genetic Algorithms and Design of Experiments in Stock Market Prediction
(2019)

Optimization of Neural Networks with Response Surface Methodology: Prediction of Cigarette Pressure Drop
(2019)